IIM Indore in collaboration with foreign teams conducts series of researches on COVID-19 pandemic

Indian Institute of Management (IIM) Indore is conducting a series of researches around COVID-19 pandemic along with collaborators from other countries.


ANI | New Delhi | Updated: 15-05-2020 23:17 IST | Created: 15-05-2020 23:17 IST
IIM Indore in collaboration with foreign teams conducts series of researches on COVID-19 pandemic
IIM Indore (Photo/Official Website). Image Credit: ANI
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By Joymala Bagchi Indian Institute of Management (IIM) Indore is conducting a series of researches around COVID-19 pandemic along with collaborators from other countries.

"These researches include predictive models for COVID-19, response analysis of leaders, ways to build organisational resilience, stress management, and developing exit strategies for MSMEs," said Prof. Himanshu Rai, Director, IIM Indore, who is also leading some of these initiatives. One of the studies observed that the state (Madhya Pradesh) and local administration had taken the necessary interventions, and the surge in infections in a majority of districts can be attributed to the increased amount of testing (MP has a current testing rate of around 1035 per million).

If the trend of infection spread had continued without necessary interventions the current number of infections in the state of Madhya Pradesh would have been more than 10,000, as opposed to the current figure of 4426. The study now aims to explore deeper aspects of the disease spread in the state.

In this series, Prof. Sayantan Banerjee, faculty, IIM Indore, is conducting a study on COVID-19 situation for different states in India along with his collaborators as a part of the COV-N Study group. "We were using a network-based epidemiological model to predict the number of infections in the state. The primary aim of that study was to project figures for the number of infections, the possible burden on the healthcare system, and suggesting actions that can be taken by the administration at that point," he said.

The study had predicted 2500 to 3000 cases by the end of April, and the observed tally stood at 2660 on April 30. Also, the recovery rate currently stands at around 48 per cent. Banerjee mentioned, "We have to focus our attention on the district level scenario, especially the spread of infection in the red zone districts."

The results of the study show much optimism. The daily average infection rate over seven days for Indore now stands at 3.13 per cent as on May 13, as opposed to 8.18 per cent on April 30. The respective figures for Bhopal and Ujjain on May 9 are 4.83 per cent (8.18 per cent on April 30) and 7.77 per cent (10.36 per cent on April 30). "One of the fundamental quantities to look at is the reproduction number and if it drops below one, that would eventually lead to contain the infection spread. We have used a Bayesian modeling approach to estimate the evolution of this R0 over time," Prof. Banerjee explained.

The reproduction number over the past one month has dropped for all the three districts considered, and the current estimates stand at 1.543 (Indore), 1.314 (Bhopal), and 1.468 (Ujjain). Apart from exploring the infection rate and the reproduction number, the study looked into the prevalence of co-morbid conditions in the districts, based on survey data provided by the National Family Health Survey (NFHS-4).

It has been found that the male populations in the red and orange zone districts have higher percentages of obesity, elevated levels of blood sugar, and high levels of blood pressure as compared with the green zone districts. "We propose to undertake a detailed study exploring the population characteristics and other health factors to arrive at valid statistical conclusions regarding the effect of the presence of co-morbid conditions and disease prevalence," Banerjee said.

As per the latest report from Union Health Ministry, Madhya Pradesh currently stands at 4426 confirmed covid positive cases. (ANI)

(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)

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